1. Field
Exemplary embodiments relate to technology for extracting feature information from nearby objects and using the extracted feature information to create a feature map for localization of a mobile robot.
2. Description of the Related Art
Several maps are used in mobile robots depending on purpose of use, but grid maps and feature maps are used the most.
Grid maps are a type of map in which a grid of fixed size is used to reflect and store the position and shape of the surrounding environment and obstacles as they are. Grid maps are very intuitive and easy to work with but have the disadvantage of drastic increase in memory required as the robot's use space becomes larger.
In contrast, feature maps detect and store only required feature information about the surrounding environment and obstacles, such as location and color, and thus do not require much memory. However, it is relatively dependent on feature detection capabilities of a system.
In order to create a feature map, a method of installing a camera in the robot and using image information obtained from the camera to extract features of surrounding objects is often used.
However, in order to localize the robot, currently extracted features must match registered features, but the image information from the camera has a problem that it is not easy to compensate for image scaling, rotation and affine curvature due to variation in lighting and robot location. Consequently, matching capability is very limited.
Accordingly, there is need for a method of creating a feature map that is less sensitive to variation in the surrounding environment and extracts feature information more efficiently.